1. Field of the Invention
The present invention relates to a visual inspection device, a visual inspection method, and a computer program which are capable of eliminating an image of a defective item from a group of stored images of items regarded as non-defective items out of images acquired by capturing inspection objects.
2. Description of Related Art
There has hitherto been developed a visual inspection method in which an image acquired by capturing an inspection object is compared with an image (standard image) of an inspection object to serve as a standard, to thereby determine whether or not the inspection object is a non-defective item. The image to serve as the standard for the determination is an image of an item determined as a non-defective item by visual inspection, and a determination threshold for the non-defective/defective determination is set, using as the standard the image of an item determined as a non-defective item.
In order to correctly determine a non-defective item as a non-defective item, setting an appropriate determination threshold for the non-defective/defective determination is important. For example, Japanese Unexamined Patent Publication No. 2005-265661 discloses an image inspection device using an image processing method of inputting a plurality of non-defective item images to set a threshold for making a non-defective/defective determination on an image of an inspection object. In Japanese Unexamined Patent Publication No. 2005-265661, learning is performed each time a non-defective item image is added, and the threshold for the non-defective/defective determination is reset, and hence an appropriate threshold can be set even when slight variations in non-defective/defective determination have occurred.
However, there has been a problem with the image inspection device using the image processing method disclosed in Japanese Unexamined Patent Publication No. 2005-265661 in that, when an image of a defective item erroneously becomes a learning object for setting the threshold, the probability of erroneously judging a non-defective item as a defective item increases, which might cause deterioration in defect detection accuracy. Conventionally, in order to avoiding mixture of an image of a defective item, the user has visually checked an image of an item and eliminated the image determined as a defective item, but visually checking all images is a very complicated operation.